1.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

1.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum          1       1.01
## LDevsum          1       1.02
## dh0              1       1.00
## dl0              1       1.00
## dl1              1       1.00
## dl2              1       1.00
## 
## Multivariate psrf
## 
## 1.01

1.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

1.4 WAIC results

2.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

2.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum      0.999      0.999
## dh0          0.999      0.999
## 
## Multivariate psrf
## 
## 0.999

2.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

2.4 WAIC results

3.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

3.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## LDevsum      0.999       1.00
## dl0          1.001       1.01
## dl1          1.004       1.02
## dl2          0.999       1.00
## 
## Multivariate psrf
## 
## 1

3.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

3.4 WAIC results